DocumentCode
604523
Title
Reasoning research on vague information based on case-based reasoning and fuzzy-based reasoning in traditional Chinese medicine diagnosis
Author
Feng Yang ; Hemin Jin ; Huimin Qi
Author_Institution
Inst. of Inf. Technol., Henan Univ. of TCM, Zhengzhou, China
fYear
2012
fDate
29-31 Dec. 2012
Firstpage
1813
Lastpage
1817
Abstract
There is a lot of vague information about TCM (Traditional Chinese Medicine) diagnosis difficult to understand through computer. Reasoning process, by coalescing of the CBR (Case-based Reasoning) and FBR (Fuzz-based Reasoning) in artificial intelligence, makes up for shortcomings of their alone, can achieve a good understanding of information in TCM diagnosis. As for the new diagnostic features, the reasoning algorithm firstly finds them in the existing case base, if fails, fuzzy reasoning mechanism will start automatically, then ultimately the credible results will be presented to the user. Facts have shown that the algorithm has good reasoning ability and can get more accurate diagnoses.
Keywords
case-based reasoning; fuzzy reasoning; medical diagnostic computing; CBR; FBR; TCM diagnosis; artificial intelligence; case-based reasoning; fuzzy reasoning mechanism; fuzzy-based reasoning; reasoning ability; reasoning algorithm; traditional Chinese medicine diagnosis; vague information; CBR; FBR; Matching degree; Membership; TCM diagnosis;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location
Changchun
Print_ISBN
978-1-4673-2963-7
Type
conf
DOI
10.1109/ICCSNT.2012.6526271
Filename
6526271
Link To Document